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TAs and Office Hours:
Justin Zhao: Mondays, 5:30pm-7pm (jxz2101@columbia.edu)
Noura Farra: Tuesdays, 4pm-5:30pm (noura@cs.columbia.edu)
Richard Chiou: Thursdays, 2:30pm-4pm (rc2758@columbia.edu)
Mohammad Sadegh Rasooli: Fridays, 4pm-5:30pm (rasooli@cs.columbia.edu)
Office hours will be held at the NLP lab (7th floor CEPSR, room 7LW1)
Announcements:
The mid-term will be on Thursday, March 5th from 1:10-2:25pm, in
702 Hamilton.
Past midterms for the class are here: fall 2011, fall 2012, fall 2013.
| Date | Topics | Video Lectures | References | Flipped Classroom Materials | |
| Week 1 (Jan 19-23) | Introduction to NLP, Language Modeling (part 1) |
Week 1 Coursera videos from Introduction (Part 1) (11:17) to Markov Processes (Part 2) (7:12) inclusive. | Sections 1.1 and 1.2 of
Notes on language modeling (required reading) |
Questions, Solutions | |
| Week 2 (Jan 28-Feb 3) | Language Modeling (part 2) | Week 1 Coursera videos from Trigram Language Models (9:40) to Summary (2:31) inclusive.
NOTE: Columbia has cancelled classes on Jan 27th due to the weather. So flipped classrooms for week 2 will be Thursday Jan 29th and Tuesday Feb 3rd. We'll continue with the Thursday/Tuesday schedule for the next few weeks. |
Sections 1.3 and 1.4 of
Notes on language modeling (required reading) |
Questions, Solutions | |
| Week 3 (Feb 4-10) | Tagging, and Hidden Markov Models | Week 2 Coursera videos from The tagging problem (10:01) to Summary (1:50) inclusive. | Notes on tagging problems, and hidden Markov models (required reading) |
Questions, Solutions | |
| Week 4 (Feb 11-17) | Parsing, and Context-free Grammars | Week 3 - Parsing, and Context-free Grammars Coursera videos from Introduction (0:28) to Examples of Ambiguity (5:56) inclusive. | Questions, Solutions | ||
| Week 5 (Feb 18-24) | Probabilistic Context-free Grammars | Week 3 - Probabilistic Context-Free Grammars (PCFGs) Coursera videos from Introduction (1:12) to The CKY Parsing Algorithm (Part 3) (10:07) inclusive. | Notes on Probabilistic Context-Free Grammars (required reading) |
Questions, Solutions | |
| Week 6 (Feb 25-March 3) | Lexicalized PCFGs | All Week 4 Coursera videos, covering Weaknesses of PCFGs and Lexicalized PCFGs | Notes on Lexicalized Probabilistic Context-Free Grammars (required reading) |
Questions, Solutions | |
| Thursday March 5th | Mid-term | ||||
| Week 7 (March 9-13) | The IBM Translation Models | Week 5 - Introduction to Machine Translation (MT) Coursera videos, covering Opening Comments (0:25) to Introduction to Statistical MT (12:31) inclusive. Week 5 - The IBM Translation Models Coursera videos, covering Introduction (3:24) to Summary (1:48) inclusive. | Notes on Statistical Machine Translation: IBM Models 1 and 2 (required reading) |
Questions, Solutions | |
| Week 8 (March 23-March 27) | Phrase-Based Translation Models | All Week 6 Coursera videos, covering Phrase-Based Translation Models and Decoding of Phrase-Based Translation Models. | Notes on Phrase-Based Translation Models (required reading) |
Questions, Solutions | |
| Week 9 (March 30-April 3) | Log-Linear Models | All Week 7 Coursera videos, covering Log-Linear Models.
|
Notes on Log-Linear Models (required reading) |
Questions, Solutions | |
| Week 10 (April 6-10) | Log-Linear Models for Tagging, and Global Linear Models | Week 8 - Log-Linear Models for Tagging (MEMMs) Coursera videos,
and
Week 9 - Global Linear Models (GLMs) Coursera videos.
|
Notes on MEMMs (Log-Linear Tagging Models) (required reading) |
Questions, Solutions | |
| Week 11 (April 13-17) | Global Linear Models for Tagging | Week 10 - GLMs for Tagging Coursera videos. | Questions, Solutions | ||
| Week 12 (April 20-24) | Global linear models for dependency parsing |
Week 10 - GLMs for Dependency Parsing
Coursera videos, and
and Week 9 - Unsupervised Learning: Brown Clustering Coursera videos.
|
Questions, Solutions | ||
| Week 13 (April 27-May 1st) | Preparation for Final | This week we will give over the fall 2014 final in the flipped classroom sections. Please spend some time going over the final before you come to the section. |